Prediction of the Bombay Stock Exchange (BSE) Market Returns Using Artificial Neural Network and Genetic Algorithm

Yusuf Perwej,Asif Perwej

doi:10.4236/jilsa.2012.42010

Abstract

Stock Market is the market for security where organized issuance and trading of Stocks take place either through exchange or over the counter in electronic or physical form. It plays an important role in canalizing capital from the investors to the business houses, which consequently leads to the availability of funds for business expansion. In this paper, we investigate to predict the daily excess returns of Bombay Stock Exchange (BSE) indices over the respective Treasury bill rate returns. Initially, we prove that the excess return time series do not fluctuate randomly. We are applying the prediction models of Autoregressive feed forward Artificial Neural Networks (ANN) to predict the excess return time series using lagged value. For the Artificial Neural Networks model using a Genetic Algorithm is constructed to choose the optimal topology. This paper examines the feasibility of the prediction task and provides evidence that the markets are not fluctuating randomly and finally, to apply the most suitable prediction model and measure their efficiency.

Highlights

It is nowadays a common notion that vast amounts of capital are traded through the Stock Markets all around the world
Our observations on the performances of these algorithms agree with the observations of Demuth and Beale [18]. They experimented on specific network structures using different data and they found that the Resilient Backpropagation converges faster than all the other algorithms we considered in our research
The means and standard deviations of the first and last generation for all repetitions are presented in the following. These results show that the Artificial Neural Network model managed to beat clearly the predictions of the RW

Summary

Introduction

It is nowadays a common notion that vast amounts of capital are traded through the Stock Markets all around the world. National economies are strongly linked and heavily influenced by the performance of their Stock Markets. The characteristic that all Stock Markets have in common is the uncertainty, which is related with their short and long term future state. This feature is undesirable for the investor but it is unavoidable whenever the Stock Market is selected as the investment tool. The best that one can do is to try to reduce this uncertainty. Stock Market Prediction (or Forecasting) is one instrument in this process

Methods

Results

Conclusion